1. Theoretical Investigation

We begin by systematically reviewing global academic literature, governmental policies, and industrial white papers on AI ethics. Our review focuses on core themes such as fairness, transparency, accountability, human dignity, and inclusivity. From this, we extract and refine the essential principles that should guide socially responsible AI.

2. Empirical Exploration through Case Studies

Real-world failures—such as AI chatbots that perpetuate bias or systems that lack transparency—offer critical insight into where existing ethical frameworks fall short. We analyze high-profile domestic and international cases to identify recurring patterns, structural blind spots, and systemic issues that ethical guidelines must address.

3. Participatory Engagement with Stakeholders

Ethics cannot be universal unless it is inclusive. We conduct nationwide surveys and multi-stakeholder interviews involving government officials, private sector leaders, nonprofit organizations, and everyday users. By comparing stakeholder priorities across sectors, we uncover the social tensions and trade-offs that need to be negotiated in any real-world implementation of AI ethics.